Triple

T18010329
Position Surface form Disambiguated ID Type / Status
Subject Georgy Sedov E430859 entity
Predicate departurePort P1521 FINISHED
Object Arkhangelsk NE NERFINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Arkhangelsk | Statement: [Georgy Sedov, departurePort, Arkhangelsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arkhangelsk
Context triple: [Georgy Sedov, departurePort, Arkhangelsk]
  • A. Arkhangelsk chosen
    Arkhangelsk is a historic port city in northern Russia on the White Sea, long serving as a key maritime gateway and administrative center of the surrounding region.
  • B. Archangelskoye
    Archangelskoye is a historic estate and former aristocratic residence near Moscow, Russia, known for its neoclassical palace, landscaped park, and role as a cultural and political retreat.
  • C. Murmansk
    Murmansk is a major Arctic port city in northwestern Russia, known for its ice-free harbor and strategic military and shipping importance.
  • D. Severodvinsk
    Severodvinsk is a Russian port city on the White Sea, known as a major center for the construction and maintenance of nuclear submarines.
  • E. Плесецк
    Плесецк — посёлок в Архангельской области России, наиболее известный как один из главных российских космодромов и центров ракетно-космических запусков.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d8b904530081908bf341d842464856 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4b51f0a488190bd34e1f9039f4dc9 completed April 19, 2026, 10:57 a.m.
Created at: April 10, 2026, 10:24 a.m.